Shape Context Matching

Shape Context Matching is a descriptor-based image matching method that characterizes the distribution of relative positions of boundary points around a reference point, enabling robust correspondence estimation by comparing shape context histograms.

123

Publications

15.4K

Citations

404

Authors

162

Institutions

Publications per year

2017–2026

23

Authors

404

  1. JM
    Jitendra Malik

    University of California, Berkeley, United States

    7 publications · 8.3K citations

    7

    h-index

  2. GM
    Giulio Mori

    Simon Fraser University, Canada

    4 publications · 1.5K citations

    4

    h-index

  3. ZD
    Zhen Dong

    Wuhan University, China

    4 publications · 357 citations

    4

    h-index

  4. SB
    Serge Belongie

    University of California San Diego, United States

    4 publications · 7.4K citations

    4

    h-index

  5. ZT
    Zhuowen Tu

    University of California, Los Angeles, United States

    3 publications · 514 citations

    3

    h-index

1–5 of 404

Venues

  1. IEEE Geoscience and Remote Sensing Letters

    GRSL · 4 publications · 123 citations

    4

    h-index

  2. 4

    h-index

  3. 3

    h-index

  4. Pattern Recognition

    3 publications · 161 citations

    3

    h-index

  5. Neurocomputing

    3 publications · 61 citations

    3

    h-index

1–5